Lagrangian particle tracking

Lagrangian particle tracking (LPT) is a method used in fluid mechanics to analyze the motion of particles when subjected to a flow field. It provides a Lagrangian perspective, in which the flow is described by tracking fluid parcels or tracers over time, rather than observing changes at fixed locations as in the Eulerian frame.

In experimental studies, LPT is typically performed using three-dimensional particle tracking velocimetry (3D-PTV). Neutrally buoyant tracer particles are introduced into the flow, and their positions are recorded using high-speed cameras and stereo reconstruction techniques. The resulting particle paths allow for the study of turbulent structures, transport phenomena, and time-resolved Lagrangian statistics.

In computational fluid dynamics, LPT refers to the numerical simulation of discrete particles embedded in a continuous flow field. The fluid phase is typically solved in an Eulerian framework, while the particle phase is resolved using Lagrangian mechanics. This approach, also termed discrete particle simulation (DPS), is particularly suited to situations where particle–fluid coupling is weak, such as dilute multiphase flows (such as aerosols), particle deposition in the human airways, and environmental particle transport. Applications of LPT also include cases where coupling is not negligible, which require more advanced numerical methods such as the discrete element method (DEM). Examples of these cases include industrial mixing, combustion modelling, sprays, and fluidized beds.

Beyond engineering and turbulence research, LPT has been widely adopted in environmental modelling. Its capacity to resolve particle motion over complex terrain and large scales makes it suitable for studying the dispersion of atmospheric pollutants. In regional air quality assessments, LPT methods have been used for both forward simulations (predicting particle transport from known sources) and inverse modelling (inferring sources from observed concentrations). These techniques have proven effective in identifying transboundary pollution pathways and assessing exposure risks.